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Full-Text Articles in Information Security

Sit Back, Relax, And Tell Me All Your Secrets, Sarah Kirk, Daniel Foreman, Cody Lee, Shannon W. Beasley Jan 2019

Sit Back, Relax, And Tell Me All Your Secrets, Sarah Kirk, Daniel Foreman, Cody Lee, Shannon W. Beasley

Journal of Cybersecurity Education, Research and Practice

The goal of this research is to describe an active learning opportunity that was conducted as a community service offering through our Center for Cybersecurity Education and Applied Research (CCEAR). As a secondary goal, the participants sought to gain real world experience by applying techniques and concepts studied in security classes. A local insurance company tasked the CCEAR with assembling a team of students to conduct penetration testing (including social engineering exploits) against company personnel. The endeavor allowed the insurance company to obtain information that would assess the effectiveness of employee training with regard to preventing the divulgence of sensitive …


Introducing The Global Data Privacy Prize, Fred H. Cate, Christopher Kuner, Orla Lynskey, Christopher Millard, Nora Ni Loideain, Dan Jerker B. Svantesson Jan 2019

Introducing The Global Data Privacy Prize, Fred H. Cate, Christopher Kuner, Orla Lynskey, Christopher Millard, Nora Ni Loideain, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.


Attacker Capability Based Dynamic Deception Model For Large-Scale Networks, Md Ali Reza Al Amin, Sachhin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua Jan 2019

Attacker Capability Based Dynamic Deception Model For Large-Scale Networks, Md Ali Reza Al Amin, Sachhin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

In modern days, cyber networks need continuous monitoring to keep the network secure and available to legitimate users. Cyber attackers use reconnaissance mission to collect critical network information and using that information, they make an advanced level cyber-attack plan. To thwart the reconnaissance mission and counterattack plan, the cyber defender needs to come up with a state-of-the-art cyber defense strategy. In this paper, we model a dynamic deception system (DDS) which will not only thwart reconnaissance mission but also steer the attacker towards fake network to achieve a fake goal state. In our model, we also capture the attacker’s capability …


Virtual Hearings And Blockchain Technology Solutions In Criminal Law, Chantell Bergquist Jan 2019

Virtual Hearings And Blockchain Technology Solutions In Criminal Law, Chantell Bergquist

Political Science Theses and Capstones

Technology has evolved and raided our personal and professional lives. Although the courts are not immune to the advancement and integration of technology, the courts are not keeping up with relevant technological advancements. Historically, courts have been hesitant to embrace new technologies despite the Federal Rules of Civil Procedure and the American Bar Association Model Rules of Professional Conduct. Rule 1 of the Federal Rules of Civil Procedure creates the right to a “just, speedy, and inexpensive determination of every action and proceeding.” Likewise, the American Bar Association Model Rules of Professional Conduct have determined attorneys must “keep abreast of …


Multimodal Approach For Malware Detection, Jarilyn M. Hernandez Jimenez Jan 2019

Multimodal Approach For Malware Detection, Jarilyn M. Hernandez Jimenez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Although malware detection is a very active area of research, few works were focused on using physical properties (e.g., power consumption) and multimodal features for malware detection. We designed an experimental testbed that allowed us to run samples of malware and non-malicious software applications and to collect power consumption, network traffic, and system logs data, and subsequently to extract dynamic behavioral-based features. We also extracted code-based static features of both malware and non-malicious software applications. These features were used for malware detection based on: feature level fusion using power consumption and network traffic data, feature level fusion using network traffic …


Impact Of Framing And Base Size Of Computer Security Risk Information On User Behavior, Xinhui Zhan Jan 2019

Impact Of Framing And Base Size Of Computer Security Risk Information On User Behavior, Xinhui Zhan

Masters Theses

"This research examines the impact of framing and base size of computer security risk information on users' risk perceptions and behavior (i.e., download intention and download decision). It also examines individual differences (i.e., demographic factors, computer security awareness, Internet structural assurance, self-efficacy, and general risk-taking tendencies) associated with users' computer security risk perceptions. This research draws on Prospect Theory, which is a theory in behavioral economics that addresses risky decision-making, to generate hypotheses related to users' decision-making in the computer security context. A 2 x 3 mixed factorial experimental design (N = 178) was conducted to assess the effect of …


If The Legislature Had Been Serious About Data Privacy..., Fred H. Cate, Christopher Kuner, Orla Lynskey, Christopher Millard, Nora Ni Loideain, Dan Jerker B. Svantesson Jan 2019

If The Legislature Had Been Serious About Data Privacy..., Fred H. Cate, Christopher Kuner, Orla Lynskey, Christopher Millard, Nora Ni Loideain, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.


Transfer Learning For Detecting Unknown Network Attacks, Juan Zhao, Sachin Shetty, Jan Wei Pan, Charles Kamhoua, Kevin Kwiat Jan 2019

Transfer Learning For Detecting Unknown Network Attacks, Juan Zhao, Sachin Shetty, Jan Wei Pan, Charles Kamhoua, Kevin Kwiat

VMASC Publications

Network attacks are serious concerns in today’s increasingly interconnected society. Recent studies have applied conventional machine learning to network attack detection by learning the patterns of the network behaviors and training a classification model. These models usually require large labeled datasets; however, the rapid pace and unpredictability of cyber attacks make this labeling impossible in real time. To address these problems, we proposed utilizing transfer learning for detecting new and unseen attacks by transferring the knowledge of the known attacks. In our previous work, we have proposed a transfer learning-enabled framework and approach, called HeTL, which can find the common …


Procure-To-Pay Software In The Digital Age: An Exploration And Analysis Of Efficiency Gains And Cybersecurity Risks In Modern Procurement Systems, Drew Lane Jan 2019

Procure-To-Pay Software In The Digital Age: An Exploration And Analysis Of Efficiency Gains And Cybersecurity Risks In Modern Procurement Systems, Drew Lane

MPA/MPP/MPFM Capstone Projects

Procure-to-Pay (P2P) softwares are an integral part of the payment and procurement processing functions at large-scale governmental institutions. These softwares house all of the financial functions related to procurement, accounts payable, and often human resources, helping to facilitate and automate the process from initiation of a payment or purchase, to the actual disbursal of funds. Often, these softwares contain budgeting and financial reporting tools as part of the offering. As such an integral part of the financial process, these softwares obviously come at an immense cost from a set of reputable vendors. In the case of government, these vendors mainly …


Understanding The Ntru Cryptosystem, Benjamin Clark Jan 2019

Understanding The Ntru Cryptosystem, Benjamin Clark

Williams Honors College, Honors Research Projects

In this paper, we will examine the NTRU Public Key Cryptosystem. The NTRU cryptosystem was created by Joseph Silverman, Jeffery Hoffstein, and Jill Pipher in 1996. This system uses truncated polynomial rings to encrypt and decrypt data. It was recently released into the public domain in 2013. This paper will describe how this cryptosystem works and give a basic understanding on how to encrypt and decrypt using this system.


Using Labeling Theory As A Guide To Examine The Patterns, Characteristics, And Sanctions Given To Cybercrimes, Brian K. Payne, Brittany Hawkins, Chunsheng Xin Jan 2019

Using Labeling Theory As A Guide To Examine The Patterns, Characteristics, And Sanctions Given To Cybercrimes, Brian K. Payne, Brittany Hawkins, Chunsheng Xin

Sociology & Criminal Justice Faculty Publications

Over the past decade, reports of cybercrime have soared across the globe. Criminologists agree that the increase in cybercrime stems from technological advancements that have changed all facets of societal interactions. While it is agreed that technology has shaped cybercrime, there is less understanding about the dynamics of cybercrime. In particular, some researchers have explored whether these offenses are simply traditional types of crime that are now carried out through different strategies, while others have argued that cybercrimes are, in fact, new types of crime. This ambiguity potentially limits prevention and intervention strategies. In an effort to build our understanding …


Design And Evaluation Of A Wearable System For Facial Privacy, Scott Griffith Jan 2019

Design And Evaluation Of A Wearable System For Facial Privacy, Scott Griffith

Theses and Dissertations

Through the increasingly common use of devices that provide ubiquitous sensor data such as wearables, mobile phones, and Internet-connected devices of the sort, privacy challenges are becoming even more significant. One major challenge that requires more focus is bystanders' privacy, as there are too few solutions that solve the issue. Of the solutions available, many of them do not give bystanders a choice in how their private data is used, Bystanders' privacy has become an afterthought when it comes to data capture in the forms of photographs, videos, voice recordings, etc. and continues to remain that way. This thesis provides …


A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall Jan 2019

A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall

Electrical & Computer Engineering and Computer Science Faculty Publications

For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools …


The Role Of Previous Discourse In Identifying Public Textual Cyberbullying, Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill Jan 2019

The Role Of Previous Discourse In Identifying Public Textual Cyberbullying, Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill

Articles

In this paper we investigate the contribution of previous discourse in identifying elements that are key to detecting public textual cyberbullying. Based on the analysis of our dataset, we first discuss the missing cyberbullying elements and the grammatical structures representative of discourse-dependent cyberbullying discourse. Then we identify four types of discourse dependent cyberbullying constructions: (1) fully inferable constructions, (2) personal marker and cyberbullying link inferable constructions, (3) dysphemistic element and cyberbullying link inferable constructions, and (4) dysphemistic element inferable constructions. Finally, we formalise a framework to resolve the missing cyberbullying elements that proposes several resolution algorithms. The resolution algorithms target …


Security Bug Report Classification Using Feature Selection, Clustering, And Deep Learning, Tanner D. Gantzer Jan 2019

Security Bug Report Classification Using Feature Selection, Clustering, And Deep Learning, Tanner D. Gantzer

Graduate Theses, Dissertations, and Problem Reports (ETD)

As the numbers of software vulnerabilities and cybersecurity threats increase, it is becoming more difficult and time consuming to classify bug reports manually. This thesis is focused on exploring techniques that have potential to improve the performance of automated classification of software bug reports as security or non-security related. Using supervised learning, feature selection was used to engineer new feature vectors to be used in machine learning. Feature selection changes the vocabulary used by selecting words with the greatest impact on classification. Feature selection was able to increase the F-Score across the datasets by increasing the precision. We also explored …


Automatic Detection Of Insecure Codes In Stack Overflow, Shifu Hou Jan 2019

Automatic Detection Of Insecure Codes In Stack Overflow, Shifu Hou

Graduate Theses, Dissertations, and Problem Reports (ETD)

As the popularity of modern social coding paradigm such as Stack Overflow grows, its potential security risks increase as well (e.g., insecure codes could be easily embedded and distributed). To address this largely overlooked issue, we bring a new insight to exploit social coding properties in addition to code content for automatic detection of insecure code snippets in Stack Overflow. To determine if the given code snippets are insecure, we not only analyze the code content, but also utilize various kinds of relations among users, badges, questions, answers, code snippets and keywords in Stack Overflow. To model the rich semantic …


Intelligent Malware Detection Using File-To-File Relations And Enhancing Its Security Against Adversarial Attacks, Lingwei Chen Jan 2019

Intelligent Malware Detection Using File-To-File Relations And Enhancing Its Security Against Adversarial Attacks, Lingwei Chen

Graduate Theses, Dissertations, and Problem Reports (ETD)

With computing devices and the Internet being indispensable in people's everyday life, malware has posed serious threats to their security, making its detection of utmost concern. To protect legitimate users from the evolving malware attacks, machine learning-based systems have been successfully deployed and offer unparalleled flexibility in automatic malware detection. In most of these systems, resting on the analysis of different content-based features either statically or dynamically extracted from the file samples, various kinds of classifiers are constructed to detect malware. However, besides content-based features, file-to-file relations, such as file co-existence, can provide valuable information in malware detection and make …


Dabke: Secure Deniable Attribute-Based Key Exchange Framework, Yangguang Tian, Yingjiu Li, Guomin Yang, Willy Susilo, Yi Mu, Hui Cui, Yinghui Zhang Jan 2019

Dabke: Secure Deniable Attribute-Based Key Exchange Framework, Yangguang Tian, Yingjiu Li, Guomin Yang, Willy Susilo, Yi Mu, Hui Cui, Yinghui Zhang

Research Collection School Of Computing and Information Systems

We introduce the first deniable attribute-based key exchange (DABKE) framework that is resilient to impersonation attacks. We define the formal security models for DABKE framework, and propose a generic compiler that converts any attribute-based key exchanges into deniable ones. We prove that it can achieve session key security and user privacy in the standard model, and strong deniability in the simulation-based paradigm. In particular, the proposed generic compiler ensures: 1) a dishonest user cannot impersonate other user's session participation in conversations since implicit authentication is used among authorized users; 2) an authorized user can plausibly deny his/her participation after secure …


Iot Forensics Curriculum: Is It A Myth Or Reality?, Bilge Karabacak, Kemal Aydin, Andy Igonor Jan 2019

Iot Forensics Curriculum: Is It A Myth Or Reality?, Bilge Karabacak, Kemal Aydin, Andy Igonor

All Faculty and Staff Scholarship

In this research paper, two questions are answered. The first question is "Should universities invest in the preparation of an IoT forensics curriculum?". The second question is "If the IoT forensics curriculum is worth investing in, what are the basic building steps in the development of an loT forensics curriculum?". To answer those questions, the authors conducted a comprehensive literature review spanning academia, the private sector, and non-profit organizations. The authors also performed semi-structured interviews with two experts from academia and the private sector. The results showed that because of the proliferation of IoT technology and the increasing number of …


Privacy-Preserving Attribute-Based Keyword Search In Shared Multi-Owner Setting, Yibin Miao, Ximeng Liu, Robert H. Deng, Robert H. Deng, Jjguo Li, Hongwei Li, Jianfeng Ma Jan 2019

Privacy-Preserving Attribute-Based Keyword Search In Shared Multi-Owner Setting, Yibin Miao, Ximeng Liu, Robert H. Deng, Robert H. Deng, Jjguo Li, Hongwei Li, Jianfeng Ma

Research Collection Yong Pung How School Of Law

Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) facilitates search queries and supports fine-grained access control over encrypted data in the cloud. However, prior CP-ABKS schemes were designed to support unshared multi-owner setting, and cannot be directly applied in the shared multi-owner setting (where each record is accredited by a fixed number of data owners), without incurring high computational and storage costs. In addition, due to privacy concerns on access policies, most existing schemes are vulnerable to off-line keyword-guessing attacks if the keyword space is of polynomial size. Furthermore, it is difficult to identify malicious users who leak the secret keys when more …


Inception: Virtual Space In Memory Space In Real Space, Peter Casey, Rebecca Lindsay-Decusati, Ibrahim Baggili, Frank Breitinger Jan 2019

Inception: Virtual Space In Memory Space In Real Space, Peter Casey, Rebecca Lindsay-Decusati, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Virtual Reality (VR) has become a reality. With the technology's increased use cases, comes its misuse. Malware affecting the Virtual Environment (VE) may prevent an investigator from ascertaining virtual information from a physical scene, or from traditional “dead” analysis. Following the trend of antiforensics, evidence of an attack may only be found in memory, along with many other volatile data points. Our work provides the primary account for the memory forensics of Immersive VR systems, and in specific the HTC Vive. Our approach is capable of reconstituting artifacts from memory that are relevant to the VE, and is also capable …


Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles Jan 2019

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles

Computer Science Faculty Publications

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library …


Managing Cyber Risks & Business Exposure In The Surface Transportation Ecosystem, Jacques R. Francoeur Jan 2019

Managing Cyber Risks & Business Exposure In The Surface Transportation Ecosystem, Jacques R. Francoeur

Mineta Transportation Institute

This report focuses on Surface Transportation (ST), both fixed and route-based, and the growing threats to their information technology (IT) infrastructures. As an industry, ST seeks to optimize the movement of people and goods, while ensuring safety and resiliency and minimizing environmental impact. Cyber threats are a powerful medium for those with the political, social, and economic motivations and wherewithal to disrupt and destroy existing ST systems. The ultimate objective is to develop a new paradigm to define, describe, design, and deploy the most effective protection, at the lowest cost, in the shortest time within the limits of available resources. …


When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li Jan 2019

When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li

Research Collection School Of Computing and Information Systems

This paper proposes the first user-independent inter-keystroke timing attacks on PINs. Our attack method is based on an inter-keystroke timing dictionary built from a human cognitive model whose parameters can be determined by a small amount of training data on any users (not necessarily the target victims). Our attacks can thus be potentially launched on a large scale in real-world settings. We investigate inter-keystroke timing attacks in different online attack settings and evaluate their performance on PINs at different strength levels. Our experimental results show that the proposed attack performs significantly better than random guessing attacks. We further demonstrate that …


Informed Trading And Cybersecurity Breaches, Joshua Mitts, Eric L. Talley Jan 2019

Informed Trading And Cybersecurity Breaches, Joshua Mitts, Eric L. Talley

Faculty Scholarship

Cybersecurity has become a significant concern in corporate and commercial settings, and for good reason: a threatened or realized cybersecurity breach can materially affect firm value for capital investors. This paper explores whether market arbitrageurs appear systematically to exploit advance knowledge of such vulnerabilities. We make use of a novel data set tracking cybersecurity breach announcements among public companies to study trading patterns in the derivatives market preceding the announcement of a breach. Using a matched sample of unaffected control firms, we find significant trading abnormalities for hacked targets, measured in terms of both open interest and volume. Our results …


Exploring Applicability Of Blockchain To Enhance Single Sign-On (Sso) Systems, Samuel Matloob Jan 2019

Exploring Applicability Of Blockchain To Enhance Single Sign-On (Sso) Systems, Samuel Matloob

UNF Graduate Theses and Dissertations

Single-Sign-On (SSO) systems usage has been on the rise exponentially. One of the major benefits of having an SSO system is to have a central authentication service, which other applications can use. However, SSO services are also prone to failure. If an SSO service becomes unavailable due to failure, every application that uses the SSO service become simultaneously inaccessible to users. The goal of this research is to explore a technique to mitigate the availability issue of the SSO by customizing its functionality, and distributing its data using blockchain technology over the network. The Blockchain data structure possesses inherent properties …


Integration Of Biometrics And Steganography: A Comprehensive Review, Ian Mcateer, Ahmed Ibrahim, Guanglou Zhang, Wencheng Yang, Craig Valli Jan 2019

Integration Of Biometrics And Steganography: A Comprehensive Review, Ian Mcateer, Ahmed Ibrahim, Guanglou Zhang, Wencheng Yang, Craig Valli

Research outputs 2014 to 2021

The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has …


Security And Accuracy Of Fingerprint-Based Biometrics: A Review, Wencheng Yang, Song Wang, Jiankun Hu, Guanglou Zhang, Craig Valli Jan 2019

Security And Accuracy Of Fingerprint-Based Biometrics: A Review, Wencheng Yang, Song Wang, Jiankun Hu, Guanglou Zhang, Craig Valli

Research outputs 2014 to 2021

Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two …


Evaluation And Understandability Of Face Image Quality Assessment, Mohammad I. Nouyed Jan 2019

Evaluation And Understandability Of Face Image Quality Assessment, Mohammad I. Nouyed

Graduate Theses, Dissertations, and Problem Reports (ETD)

Face image quality assessment (FIQA) has been an area of interest to researchers as a way to improve the face recognition accuracy. By filtering out the low quality images we can reduce various difficulties faced in unconstrained face recognition, such as, failure in face or facial landmark detection or low presence of useful facial information. In last decade or so, researchers have proposed different methods to assess the face image quality, spanning from fusion of quality measures to using learning based methods. Different approaches have their own strength and weaknesses. But, it is hard to perform a comparative assessment of …


Agent-Based Iot Coordination For Smart Cities Considering Security And Privacy, Iván García-Magariño, Geraldine Gray, Rajarajan Muttukrishnan, Waqar Asif Jan 2019

Agent-Based Iot Coordination For Smart Cities Considering Security And Privacy, Iván García-Magariño, Geraldine Gray, Rajarajan Muttukrishnan, Waqar Asif

Conference papers

The interest in Internet of Things (IoT) is increasing steeply, and the use of their smart objects and their composite services may become widespread in the next few years increasing the number of smart cities. This technology can benefit from scalable solutions that integrate composite services of multiple-purpose smart objects for the upcoming large-scale use of integrated services in IoT. This work proposes an agent-based approach for supporting large-scale use of IoT for providing complex integrated services. Its novelty relies in the use of distributed blackboards for implicit communications, decentralizing the storage and management of the blackboard information in the …